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TVL1 Planarity Regularization for 3D Shape Approximation

Funk, Eugen; Dooley, Laurence S. and Börner, Anko (2016). TVL1 Planarity Regularization for 3D Shape Approximation. In: Braz, José; Pettré, Julien; Richard, Paul; Kerren, Andreas; Linsen, Lars; Battiato, Sebastiano and Imai, Francisco eds. Computer Vision, Imaging and Computer Graphics Theory and Applications. Communications in Computer and Information Science, 598. Berlin: Springer International Publishing, pp. 274–294.

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URL: http://link.springer.com/book/10.1007/978-3-319-29...
DOI (Digital Object Identifier) Link: https://doi.org/10.1007/978-3-319-29971-6_15
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Abstract

The modern emergence of automation in many industries has given impetus to extensive research into mobile robotics. Novel perception technologies now enable cars to drive autonomously, tractors to till a field automatically and underwater robots to construct pipelines. An essential requirement to facilitate both perception and autonomous navigation is the analysis of the 3D environment using sensors like laser scanners or stereo cameras. 3D sensors generate a very large number of 3D data points when sampling object shapes within an environment, but crucially do not provide any intrinsic information about the environment which the robots operate within.

This work focuses on the fundamental task of 3D shape reconstruction and modelling from 3D point clouds. The novelty lies in the representation of surfaces by algebraic functions having limited support, which enables the extraction of smooth consistent implicit shapes from noisy samples with a heterogeneous density. The minimization of total variation of second differential degree makes it possible to enforce planar surfaces which often occur in man-made environments. Applying the new technique means that less accurate, low-cost 3D sensors can be employed without sacrificing the 3D shape reconstruction accuracy.

Item Type: Book Section
Copyright Holders: 2016 Springer International Publishing Switzerland
ISBN: 3-319-29970-0, 978-3-319-29970-9
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM)
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Related URLs:
Item ID: 45399
Depositing User: Laurence Dooley
Date Deposited: 04 Mar 2016 14:14
Last Modified: 12 Feb 2017 01:00
URI: http://oro.open.ac.uk/id/eprint/45399
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